Modern inventory systems, such as those in mail order warehouses, supply chain distribution centers, and custom-order manufacturing facilities, face significant challenges in preventing collisions between inventory management components. As inventory systems grow, the challenges of simultaneously completing a large number of packing, storing, and other inventory-related tasks while avoiding collisions become non-trivial. In inventory systems tasked with responding to large numbers of diverse inventory requests, inefficient utilization of system resources, including space, equipment, and manpower, can result in inventory components (e.g., robotic units) traveling along a number of different routes. Increasing the number of requests to inventory management system components may increase the risk of collision dramatically.
Collision detection typically refers to the computational problem of detecting the intersection of two or more objects. Conventional approaches to collision detection for multiple objects are often very slow and resource intensive. Checking every object against every other object will work, but is often too inefficient to be used when the number of objects is large. This inefficiency is increased with when checking objects with complex geometry against each other. Thus, considerable research has been applied to speed up the problem.